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Record W2996939753 · doi:10.1109/tbc.2019.2954065

Mobile Performance Evaluation for ATSC 3.0 Physical Layer Modulation and Code Combinations Under TU-6 Channel

2020· article· en· W2996939753 on OpenAlexaff
Sungjun Ahn, Sung-Ik Park, Jae-Young Lee, Bo-mi Lim, Sunhyoung Kwon, Namho Hur, Yiyan Wu, Liang Zhang, Wei Li, Jeongchang Kim

Bibliographic record

VenueIEEE Transactions on Broadcasting · 2020
Typearticle
Languageen
FieldEngineering
TopicTelecommunications and Broadcasting Technologies
Canadian institutionsCommunications Research Centre Canada
Fundersnot available
KeywordsPhysical layerComputer scienceChannel (broadcasting)Multipath propagationCode (set theory)Computer networkModulation (music)Broadcasting (networking)Digital Video BroadcastingLayer (electronics)Electronic engineeringTelecommunicationsEngineeringWirelessSet (abstract data type)

Abstract

fetched live from OpenAlex

This paper presents performance analysis of the Advanced Television Systems Committee (ATSC) 3.0 physical layer protocol in mobile multipath channels. Given the recommended configurations for ATSC 3.0 mobile services, intensive computer simulations as well as laboratory tests are conducted to verify the performance of various modulation and code combinations in ATSC 3.0 physical layer protocol. The results demonstrate that the ATSC 3.0 physical layer can reliably deliver intended mobile services in high-mobility scenarios.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.067
GPT teacher head0.283
Teacher spread0.216 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations33
Published2020
Admission routes1
Has abstractyes

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